% Copyright (C) 2019-2023 Benjamin Born, Francesco D'Ascanio, Gernot J. Mueller, Johannes Pfeifer
%
% This is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% It is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
% GNU General Public License for more details.
%
% For a copy of the GNU General Public License,
% see <http://www.gnu.org/licenses/>.

% Run LPs conditioning on slack

function run_LP_slack(sign_iter)

if sign_iter==1
    sign_dummy = -1;
elseif sign_iter==2
    sign_dummy = 1;
else
    error('Case not implemented')
end

if ~isfolder('Figures')
    mkdir('.','Figures');
end
addpath('../Auxiliary_Files')
fontsize = 6;

figures_name = 'Figures';

lag_number=4;
max_irf_horizon = 8;
time_fixed_effects_dummy=1;
country_fixed_effects_dummy=1;

add_residual_dummy=1; %adds residuals from previous step to regression to increase efficiency;

%the naming of the following needs to be consistent with the field names in the pos structure
impulse_name = 'PF_shock_G';
special_name = 'pf_fc';

%% Construct sample

% Load data arrays for regression
load('../Figure 3+6 + Appendix C Descriptives/dataset_BDMP.mat')
temp=load('../Sign_restriction_first_stage_shocks_euro_area/results/structural_shocks_point.mat');

data_array_for_regression_stacked_by_variable = cat(3,data_array_for_regression_stacked_by_variable,temp.structural_shocks.BP_G,temp.structural_shocks.BP_T,temp.structural_shocks.PF_G,temp.structural_shocks.PF_T);
pos.BP_shock_G_CK=length(fieldnames(pos))+1;
Header{1,pos.BP_shock_G_CK}='BP_shock G based on Caldara/Kamps';
pos.BP_shock_T_CK=length(fieldnames(pos))+1;
Header{1,pos.BP_shock_T_CK}='BP_shock T based on Caldara/Kamps';
pos.PF_shock_G=length(fieldnames(pos))+1;
Header{1,pos.PF_shock_G}='Sign restriction shock G based on Caldara/Kamps';
pos.PF_shock_T=length(fieldnames(pos))+1;
Header{1,pos.PF_shock_T}='Sign restriction shock T based on Caldara/Kamps';

if length(Header)~=length(fieldnames(pos)) ||  length(Header)~=size(data_array_for_regression_stacked_by_variable,3)
    error('Header is not correctly defined')
end

% check whether positions are unique
pos_numbers=cell2mat(struct2cell(pos));
unique_pos_numbers=unique(pos_numbers);
if ~isequal(pos_numbers,unique_pos_numbers)
    pos_numbers(~ismember(pos_numbers,unique_pos_numbers))
    error('The position numbers are wrong')
end
% Set dependent variables and regressors
regressor_var_names={'g_real_demeaned_linearly_detrended', 'y_real_demeaned_linearly_detrended', 'Effective_FX_Real_Intra_Euro_CPI_log', 'tax_revenue_real_demeaned_detrended'};
dependent_var_names={'g_real_demeaned_linearly_detrended','y_real_demeaned_linearly_detrended','Effective_FX_Real_Intra_Euro_CPI_log', 'tax_revenue_real_demeaned_detrended'};
dependent_var_plottitles={'Government consumption','GDP','Real Effective Exchange Rate', 'Tax revenues'};
dependent_var_ylabels={'percent','percent','percent', 'percent'};
special_name = ['real_fx_intra_euro',special_name];

if lag_number<1
    error('Lag number must be strictly positive')
end

% Float
[row,col] =find(data_array_for_regression_stacked_by_variable(:,:,pos.Indicator_unemployment_rate_above_percentile_50)~=1);
split_save_name='unemp_perc';
Figure_name_split='Unemployment sample';
State_name_vector={'Labor market slack', 'Full sample'};

for ii=1:length(row)
    data_array_for_regression_stacked_by_variable(row(ii),col(ii),3:end)=NaN;
end

%% Shock Variable
fe_shocks_temp = data_array_for_regression_stacked_by_variable(:,:,pos.(impulse_name));

fe_shocks_negative = zeros(size(fe_shocks_temp));
fe_shocks_negative(fe_shocks_temp<0 | isnan(fe_shocks_temp)) = fe_shocks_temp(fe_shocks_temp<0 | isnan(fe_shocks_temp));
fe_shocks_positive = zeros(size(fe_shocks_temp));
fe_shocks_positive(fe_shocks_temp>0 | isnan(fe_shocks_temp)) = fe_shocks_temp(fe_shocks_temp>0 | isnan(fe_shocks_temp));
if any(any(fe_shocks_negative>0)) || any(any(fe_shocks_positive<0 ))
    error('Sign is wrong')
end

if sign_dummy==-1
    data_array_for_regression_impulse_only=cat(3,fe_shocks_negative,fe_shocks_positive);
elseif sign_dummy==1
    data_array_for_regression_impulse_only=cat(3,fe_shocks_positive,fe_shocks_negative);
elseif sign_dummy==0
    data_array_for_regression_impulse_only=cat(3,fe_shocks_temp);
else
    error('undefined case for sign_dummy')
end

data_array_for_regression=data_array_for_regression_impulse_only;

%% Lagged regressors

for var_iter=1:length(regressor_var_names)
    data_array_control=data_array_for_regression_stacked_by_variable(:,:,pos.([regressor_var_names{var_iter},'_lag_1']):pos.([regressor_var_names{var_iter},'_lag_',num2str(lag_number)]));
    data_array_for_regression=cat(3,data_array_for_regression,data_array_control);
end

%% Run regression

theta_mat=NaN(1+max_irf_horizon,1,length(dependent_var_names));
se_mat=NaN(1+max_irf_horizon,1,length(dependent_var_names));

for var_iter=1:length(dependent_var_names)
    for horizon_iter = 0:max_irf_horizon
        %construct matrices without NaN
        if horizon_iter==0
            dependent_variable=squeeze(data_array_for_regression_stacked_by_variable(:,:,pos.(dependent_var_names{var_iter})));
            yhat_full=NaN(size(dependent_variable));
            [dependent_variable_for_run,data_array_for_regression_for_run,time_indices_non_NaN,country_indices_non_NaN]=create_regression_matrices_no_NaN(dependent_variable,data_array_for_regression,data_array_for_regression_stacked_by_variable,pos,country_indicator_names_mapping,time_fixed_effects_dummy,country_fixed_effects_dummy);
            %run regression
            [theta,stdDK,~,CovDK,yhat] = HszDk5cPs(dependent_variable_for_run,ones(size(dependent_variable_for_run,1),1),data_array_for_regression_for_run,1,7,1);

            if add_residual_dummy && ~strcmp(impulse_name,dependent_var_names(var_iter)) %when regression G on itself, residuals are 0
                yhat_full(time_indices_non_NaN,country_indices_non_NaN)=yhat;
                resids=dependent_variable-yhat_full;
            else
                resids=[];
            end
        else
            dependent_variable=squeeze(data_array_for_regression_stacked_by_variable(:,:,pos.([dependent_var_names{var_iter},'_lead_',num2str(horizon_iter)])));
            yhat_full=NaN(size(dependent_variable));

            [dependent_variable_for_run,data_array_for_regression_for_run,time_indices_non_NaN,country_indices_non_NaN]=create_regression_matrices_no_NaN(dependent_variable,cat(3,data_array_for_regression,resids),data_array_for_regression_stacked_by_variable,pos,country_indicator_names_mapping,time_fixed_effects_dummy,country_fixed_effects_dummy);
            %run regression
            [theta,stdDK,~,CovDK,yhat] = HszDk5cPs(dependent_variable_for_run,ones(size(dependent_variable_for_run,1),1),data_array_for_regression_for_run,1,7,1);
            if add_residual_dummy
                yhat_full(time_indices_non_NaN,country_indices_non_NaN)=yhat;
                resids=dependent_variable-yhat_full;
            else
                resids=[];
            end
        end

        %save coefficients
        theta_mat(1+horizon_iter,:,var_iter) = theta(1,1);
        se_mat(1+horizon_iter,:,var_iter)  = stdDK(1,1)';
        Rmat = zeros(1,length(theta));
        Rmat(1,1:2) = [1,-1];
        Wstat = (Rmat*theta)'/(Rmat*CovDK*Rmat')*(Rmat*theta);
        test_p_mat(1+horizon_iter, var_iter) = 1 - chi2cdf(Wstat,1);
        if sign_dummy== 1
            if horizon_iter<5 && var_iter==2
                theta_table(1,1+horizon_iter) = -100 * theta(1,1);
                theta_table(2,1+horizon_iter) = 100 * stdDK(1,1);
                theta_table(3,1+horizon_iter) = (1-normcdf(abs(theta(1,1))./stdDK(1,1)))*2;

                theta_table(4,1+horizon_iter) = 100 * theta(2,1);
                theta_table(5,1+horizon_iter) = 100 * stdDK(2,1);
                theta_table(6,1+horizon_iter) = (1-normcdf(abs(theta(2,1))./stdDK(2,1)))*2;

                theta_table(7,1+horizon_iter) = 100 * (theta(1,1) - theta(2,1));
                theta_table(8,1+horizon_iter) = test_p_mat(1+horizon_iter, var_iter);

            elseif horizon_iter<5 && var_iter==3
                theta_table(1,1+horizon_iter+5) = 100 * theta(1,1);
                theta_table(2,1+horizon_iter+5) = 100 * stdDK(1,1);
                theta_table(3,1+horizon_iter+5) = (1-normcdf(abs(theta(1,1))./stdDK(1,1)))*2;

                theta_table(4,1+horizon_iter+5) = -100 * theta(2,1);
                theta_table(5,1+horizon_iter+5) = 100 * stdDK(2,1);
                theta_table(6,1+horizon_iter+5) = (1-normcdf(abs(theta(2,1))./stdDK(2,1)))*2;

                theta_table(7,1+horizon_iter+5) = -100 * (theta(1,1) - theta(2,1)); %minus to account for definition of FX in Eurostat data, which is the opposite of the one in the paper
                theta_table(8,1+horizon_iter+5) = test_p_mat(1+horizon_iter, var_iter);
            end
            if horizon_iter==5 && var_iter==3
                headers_string=char('\psi_{h}^{-} - \psi_{h}^{+}','0','1','2','3','4');
                labels_string=char('Output','p-val','REER','p-val');
                dyntable('moments_peg',headers_string,labels_string,[theta_table(7:8,1:5); theta_table(7:8,6:end)],size(labels_string,2)+2,5,2)
            end
        end

    end
end

%% Plot IRFs

if length(dependent_var_names) == 3
    if sign_dummy == -1
        subplot_index = [1,4,7];
    elseif sign_dummy == 1
        subplot_index = [2,5,8];
    else
        error('not defined')
    end
    startsp = 1;
elseif length(dependent_var_names) == 4
    if sign_dummy == -1 || sign_dummy == 0
        subplot_index = [1,4,7,10,];
    elseif sign_dummy == 1
        subplot_index = [2,5,8,11];
    else
        error('not defined')
    end
    startsp = 1;
elseif length(dependent_var_names) == 5
    if sign_dummy == -1 || sign_dummy == 0
        subplot_index = [1,4,7,10,13];
    elseif sign_dummy == 1
        subplot_index = [2,5,8,11,14];
    else
        error('not defined')
    end
    startsp = 1;
else
    error('Specify Subplot Layout')
end


if sign_dummy == -1
    scaling = -100; % cut in government spending
    sign_plottitle = 'Gov. consumption cut';
elseif sign_dummy == 1
    scaling = 100; % increase in government spending
    sign_plottitle = 'Gov. consumption hike';
elseif sign_dummy == 0
    scaling = 100; % increase in government spending
    sign_plottitle = 'Gov. consumption cut (symmetric model)';
end

nptsvar=max_irf_horizon;
confidence_90  = norminv(0.9 + (1 - 0.9) / 2, 0, 1);
confidence_68  = norminv(0.68 + (1 - 0.68) / 2, 0, 1);

if sign_dummy == -1 || sign_dummy == 0
    main_fig = openfig(['../Figure 3+6 + Appendix C Descriptives/Figures/eur_asym_pos_real_fx_intraeuro_pf_fc']);
elseif sign_dummy == 1
    main_fig = openfig([figures_name,filesep,split_save_name,'_asym_neg_',special_name]);
else
    error('not defined yet')
end


plot_iter = 1;
for sp = startsp:length(dependent_var_names)
    if sp == 3
        scaling = scaling * -1; %account for definition of FX in BIS data, which is the opposite of the one in the paper
    end
    figure(main_fig)

    subplot(5,3,subplot_index(plot_iter))

    ci1b_90 = scaling*(theta_mat(:,1,sp)+confidence_90*se_mat(:,1,sp));
    ci2b_90 = scaling*(theta_mat(:,1,sp)-confidence_90*se_mat(:,1,sp));
    ci1b_68 = scaling*(theta_mat(:,1,sp)+confidence_68*se_mat(:,1,sp));
    ci2b_68 = scaling*(theta_mat(:,1,sp)-confidence_68*se_mat(:,1,sp));

    topb_90 = max(ci1b_90,ci2b_90);
    bottomb_90 = min(ci1b_90,ci2b_90);
    topb_68 = max(ci1b_68,ci2b_68);
    bottomb_68 = min(ci1b_68,ci2b_68);

    ha1_90 = area(0:nptsvar,[bottomb_90, topb_90-bottomb_90],'FaceColor',[1 204/255 204/255],'EdgeColor','none','ShowBaseLine','off');
    set(ha1_90(1), 'FaceColor', 'none') % this makes the bottom area invisible
    set(ha1_90, 'LineStyle', '-')
    ha1_90(2).FaceAlpha = 0.5;
    hold on
    ha1_68 = area(0:nptsvar,[bottomb_68, topb_68-bottomb_68],'FaceColor',[1 0.6 0.6],'EdgeColor','none','ShowBaseLine','off');
    set(ha1_68(1), 'FaceColor', 'none') % this makes the bottom area invisible
    set(ha1_68, 'LineStyle', '-')
    ha1_68(2).FaceAlpha = 0.5;

    fs=plot(0:nptsvar,scaling*theta_mat(:,1,sp),'r--', 'LineWidth', 2.5);

    hline(0,'k:')
    xlim([0 max_irf_horizon])
    box on;set(gca,'xTick',0:max_irf_horizon,'Layer','top','FontSize',fontsize);

    title(dependent_var_plottitles(sp),'FontSize',fontsize)
    ylabel(dependent_var_ylabels(sp),'FontSize',fontsize)
    xlabel('quarters','FontSize',fontsize)
    plot_iter = plot_iter + 1;
    if sp == 3
        scaling = scaling * -1;
    end
end

set(findall(main_fig,'-property','ShowBaseLine'),'ShowBaseLine','off')

% save main figure
if sign_dummy==-1
    saveas(main_fig,[figures_name,filesep,split_save_name,'_asym_neg_',special_name]);
    print([figures_name,filesep,split_save_name,'_asym_neg_',special_name],'-depsc2')
    close(main_fig)
elseif sign_dummy==1
    set(main_fig,'Units','Inches');
    set(main_fig,'Name','Slack')
    pos = get(main_fig,'Position');
    set(main_fig,'PaperPositionMode','Auto','PaperUnits','Inches','PaperSize',[pos(3), pos(4)])
    saveas(main_fig,[figures_name,filesep,split_save_name,'_asym_pos_',special_name]);
    print([figures_name,filesep,split_save_name,'_asym_pos_',special_name],'-dpdf')
elseif sign_dummy==0
    saveas(main_fig,[figures_name,filesep,split_save_name,'_',indicator_save_name,'_sym_',special_name]);
    print([figures_name,filesep,split_save_name,'_',indicator_save_name,'_sym_',special_name],'-depsc2')
end